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Determining future thunderstorm-prone environments in Southern Ontario by using statistical downscaling to project changes in convective available potential energy (CAPE)

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Considering the potential risks associated with thunderstorms, to date, there has been limited analysis on the projection of thunderstorm occurrence trends in Canada. The small spatial and temporal scales of thunderstorms are not resolved in global climate models (GCMs). In this study, the relationship is established between thunderstorm observations from nine weather stations across Southern Ontario, Canada, and daily maximum convective available potential energy (CAPE). The results from the correlation analysis between CAPE and thunderstorm days suggested that the probability of observing a thunderstorm increases as maximum daily CAPE increases. We then utilize the novel approach of applying statistical downscaling (SDSM) to CAPE. After regenerating CAPE over a 30-year reference period (1981–2010) at each weather station, it was determined that the SDSM-modeled CAPE values well compared to observed CAPE values. Future CAPE values up to the end of the current century are then projected using the SDSM models for each station in combination with three GCMs for future climate. The forecast from the downscaling suggested large increases, as much as tripling, in annual mean CAPE, summer mean CAPE, and number of days exceeding a 50% probability and 80% probability of observing a thunderstorm at all weather stations under SRES business-as-usual and RCP 8.5 scenarios for the study period of 2011–2100. All else being equal, this suggests an increase in the number of days with conditions favorable for thunderstorms under a warmer climate.

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  • Allen JT, Karoly DJ, Walsh KJ (2014a) Future Australian severe thunderstorm environments. Part I: A novel evaluation and climatology of convective parameters from two climate models for the late twentieth century. J Clim 27(10):3827–3847

    Article  Google Scholar 

  • Allen JT, Karoly DJ, Walsh KJ (2014b) Future Australian severe thunderstorm environments. Part II: The influence of a strongly warming climate on convective environments. J Clim 27(10):3848–3868

    Article  Google Scholar 

  • Brooks HE, Carbin GW, Marsh PT (2014) Increased variability of tornado occurrence in the United States. Science 346(6207):349–352

    Article  Google Scholar 

  • Brooks HE, Lee JW, Craven JP (2003) The spatial distribution of severe thunderstorm and tornado environments from global reanalysis data. Atmos Res 67-68:73–94

    Article  Google Scholar 

  • Chen J, Brissette FP, Leconte R (2012) Coupling spatial and dynamical methods for downscaling precipitation. Clim Chang 114(3-4):509–526

    Article  Google Scholar 

  • Craven JP, Brooks HE (2004) Baseline climatology of sounding derived parameters associated with deep moist convection. National Weather Digest 28:13–24

    Google Scholar 

  • Desu MM, Raghavarao D (2004) Nonparametric statistical methods for complete and censored data. Chapman & Hall

  • Dieffenbaugh NS, Scherer M, Trapp RJ (2013) Robust increases in severe thunderstorm environments in response to greenhouse forcing. Proc Natl Acad Sci U S A 110(41):16361–16366

    Article  Google Scholar 

  • Elsner JB, Elsner SC, Jagger TH (2014) The increasing efficiency of tornado days in the United States. Clim Dyn.

  • Etkin D, Brun SE, Shabbar A, Joe P (2001) Tornado climatology of Canada revisited: tornado activity during different phases of ENSO. Int J Climatol 21:915–938

    Article  Google Scholar 

  • Environment Canada (2013) Canada’s top ten weather stories for 2004. Retrieved from: Retrieved: October 2013

  • Environment Canada, 2014. Canadian Centre for Climate Modelling and Analysis. The Third Generation Coupled Global Climate Model. Retrieved from: Retrieved: October 2015.

  • Gensini VA, Mote TL (2014) Estimations of hazardous convective weather in the United States using dynamical downscaling. J Clim 27:6581–6589.

    Article  Google Scholar 

  • Gough WA, Mohsin T (2006) Climatological perspective on the Peterborough flood. CMOS Bulletin 34:39–42

    Google Scholar 

  • Hirsch RM, Slack JR, Smith RA (1982) Techniques of trend analysis for monthly water quality data. Water Resour Res 18:107–121

    Article  Google Scholar 

  • Holley DM, Dorling SR, Steele CJ, Earl N (2014) A climatology of convective available potential energy in Great Britain. Int J Climatol 34:3811–3824

    Article  Google Scholar 

  • Holton JR (2004) An introduction to dynamic meteorology, 4th edn. Elsevier Academic Press

  • Hosmer DW, Lemeshow S (1989) Applied logistic regression. John Wiley & Sons Ltd.

  • Huryn S, Gough W, Butler K, Mohsin T (2015) An evaluation of thunderstorm observations in Southern Ontario using automated lightning detection data. J Appl Meteorol Climatol 54(9):1837–1846

    Article  Google Scholar 

  • Huryn S, Gough W, Butler K (2016) A review of thunderstorm trends across Southern Ontario from the 1950s to 2011. Atmosphere-Ocean In Press

  • IPCC AR5 Intergovernmental Panel on Climate Change Fifth Assessment Report. Chapter 9: Evaluation of climate models. Retrieved from: Retrieved: October 2015.

  • Insurance Bureau of Canada (2014) Canada inundated by severe weather in 2013: insurance companies pay out record-breaking $3.2 billion to policyholders. Retrieved from:

  • King PWS (1996) A long lasting squall line induced by interacting lake breezes. Preprints. In: 18thConference on Severe Local Storms, San Francisco, CA. American Meteorological Society, pp 764–767

  • King, P.W.S., Leduc, M.J., Sills, D.M.L., Donaldson, N.R., Hudak., D.R., Joe, P. & Murphy, B.P. (2003). Lake breezes in Southern Ontario and their relation to tornado climatology. Weather Forecast 18(5), 795-807.

  • Kirkpatrick C, McCaul EW, Cohen C (2011) Sensitivities of simulated convective storms to environmental CAPE. Mon Weather Rev 139:3514–3532

    Article  Google Scholar 

  • Lock NA, Houston AL (2014) Empirical examination of the factors affecting thunderstorm initiation. Mon Weather Rev 142(1):240–258

    Article  Google Scholar 

  • Mesinger, F. DiMego, G., Kalnay, E., Mitchell, K., Shafran, P.C. Ebisuzaki, W. Jovic, D. Woollen, J. Rogers, E., Berbery, E.H. Ek,M.B. Fan, Y. Grumbine, R. Higgins, W. Li, H. Lin, Y. Manikin, G. Parrish, D. & W. Shi. 2004. North American Regional Reanalysis. Bull Am Meteorol Soc, 4189-4201.

  • Mills B, Unrau D, Pentelow L, K. (2010) Assessment of lightning-related damage and disruption in Canada. Nat Hazards 52:481–499

    Article  Google Scholar 

  • Mills B, Unrau D, Parkinson C, Jones B, Yessis J, Spring K, Pentelow L (2008) Assessment of lightning-related fatality and injury risk in Canada. Nat Hazards 47(2):157–183

    Article  Google Scholar 

  • Mohsin T, Gough WA (2010) Trend analysis of long-term temperature time series in the Greater Toronto Area (GTA). Theor Appl Climatol 101:311–327

    Article  Google Scholar 

  • Moller AR (2001) Severe local storms forecasting. Meteorol Monogr 28(50):433–480

    Article  Google Scholar 

  • Morrsion MJ, Kopp GA, Gavanski E, Miller C, Ashton A (2014) Assessment of damage to residential construction from the tornadoes in Vaughan, Ontario, on 20 August 2009. Can J Civ Eng 41(6):550–558

    Article  Google Scholar 

  • NOAA (2009). Glossary: CAPE. In: National Oceanographic and Atmospheric Administration’s National Weather Service. Retrieved: November 2015

  • Paquin D, de Elia R, Frigon A (2014) Change in North American atmospheric conditions associated with deep convection and severe weather using CRCM4 climate projections. Atmosphere-Ocean 52(3):175–190

    Article  Google Scholar 

  • Rasmussen EN, Blanchard DO (1998) A baseline climatology of sounding-derived supercell and tornado forecast parameters. Weather Forecast 13:1148–1164

    Article  Google Scholar 

  • Sen PK (1968) Estimates of the regression coefficient based on Kendall’s tau. J Am Stat Assoc 63:1379–1389

    Article  Google Scholar 

  • Sills DML, Brook JR, Levy I, Makar PA, Zhang J, Taylor PA (2011) Lake breezes in the southern Great Lakes region and their influence during BAQS-Met 2007. Atmos Chem Phys 11:7955–7973

    Article  Google Scholar 

  • Sills, D.M.L. & King, P.W.S. (1998). The 1997 ELBOW Project: high-resolution modeling of lake breezes in a pre-storm environment. Preprints. 19thConference on Severe Local Storms, Minneapolis, MN, American Meteorological Society, 23-26.

  • Statistics Canada, 2012: The Canadian population in 2011: population counts and growth. Catalogue no. 98-310-X2011001 Retrieved from:

  • Tippett MK, Cohen JE (2014) Tornado outbreak variability follows Taylor’s power law of fluctuation scaling and increases dramatically with severity. Nat Commun 7.

  • Trapp, R. J., Diffenbaugh, N. S., Brooks, H. E., Baldwin, M. E., Robinson, E. D., & Pal, J. S. (2007). Changes in severe thunderstorm environment frequency during the 21st century caused by anthropogenically enhanced global radiative forcing. Proceedings of the National Academy of Sciences of the United States of America, 104, 19719-19723.

  • UK MetOffice (2013) Government of the United Kingdom Met Office. Met Office climate prediction model, HadGEM. Retrieved from:

  • Van Klooster SL, Roebber PJ (2009) Surface-based convective potential in the contiguous United States in a business-as-usual future climate. J Am Meteorol Soc 22:3317–3330

    Google Scholar 

  • Wilby, R.L., Dawson, C.W. & E.M. Barrow. (2002). SDSM—a decision support tool for the assessment of regional climate change impacts. Environ Model Softw 17, 145–157.

  • Wilby RL, Dawson, C. W. (2001) Using SDSM—a decision support tool for the assessment of regional climate change impacts. User manual prepared on behalf of the Environment Agency, Risk Analysis Section (

  • Wilby, R.W. & C.W. Dawson (2007) SDSM 4.2—a decision support tool for the assessment of regional climate change impacts. User manual.

  • Wilby RL, Dawson CW (2013) The Statistical Downscaling Model (SDSM): insights from one decade of application. Int J Climatol 33:1707–1719

    Article  Google Scholar 

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Correspondence to Tanzina Mohsin.

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Huryn, S.M., Mohsin, T., Gough, W.A. et al. Determining future thunderstorm-prone environments in Southern Ontario by using statistical downscaling to project changes in convective available potential energy (CAPE). Theor Appl Climatol 141, 1235–1249 (2020).

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